New mathematical algorithms and computer programs will be developed and applied to the metric analysis of genetic sequences related to cancer. Previously we have described an algorithm and a computer program for calculating the evolutionary distance and determining each metric alignment between two specified genetic sequences. Recently we have developed an algorithm and computer program for finding the best ways to align a specified sequence with any segment of a larger sequence. Currently we are devising an algorithm and program to find the best ways to align all segments of one sequence with all segments of another. Even though these procedures consider all possible ways to insert gaps in both sequences, they each require only on the order of N2 steps, where N is the length of a sequence. These computer programs are not only very efficient but, in the latter two cases, unique tools for recognition of normal and abnormal patterns in genetic sequences. We intend to use these new methods to search for common patterns among the currently available genetic sequences related to cancer. Protein sequences, including those of histocompatibility antigens, immunoglobulins, and complement components, will be compared to discover related segments that may suggest similar biological functions. These methods will also be used to facilitate the sequencing of certain proteins, such as the thymic leukemia antigen. DNA sequences will be analyzed to define the common structural features of the sites for various restriction enzymes, DNA polymerases, and RNA splicing enzymes. These results will be useful in defining the active sites of protein and nucleic acid sequences and in locating structural abnormalities that may be responsible in part for cancer.